\([\tilde{c};\tilde{f_i}]\)  is the transformer-based encoding of \(c\)  concatenated to \(f_i\) . The question generation component in Varifocal is similar to the answer-aware sequence-to-sequence model [1]}. But, the generator is trained to use focal points instead of answers to the questions that need to be generated. While focal points act similarly to prompts [2]}, [3]}, [4]}, we typically have multiple focal points that are different for each claim, depending on the complexity of its parse tree, as opposed to a small number of fixed prompts, such as one per label in classification tasks.
